Variational methods in elasticity and plasticity

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Multibody Systems Approach To Vehicle Dynamics

Dynamic simulation patterns and spatiotemporal analysis of land-use/land-cover changes in the Wuhan metropolitan area, China

An integrated approach of logistic-MCE-CA-Markov to predict the land use structure and their micro-spatial characteristics analysis in Wuhan metropolitan area, Central China

Hard landings account for a large proportion of aircraft accidents and are generally judged by the intuition of pilots. For this reason, there are frequent false judgments that lead to unnecessary and costly ground inspections. False judgments can be reduced significantly if detailed load information is available, such as strains or loads on critical areas of aircraft structures. This study used an artificial neural network (ANN) to develop a numerical model that can estimate the maximum strains for areas of interest and landing loads from basic flight parameters. The results can be used to provide the required detailed load information. An efficient and accurate landing simulation model was constructed and used to build reliable datasets for training. Basic flight parameters from immediately after touchdown were used as input data for training, and the corresponding maximum values of strains and landing loads were obtained from the landing simulation model as target data for training. This information was used to train the ANNs with the Levenberg–Marquardt backpropagation algorithm. A performance evaluation using test data confirmed that the trained ANNs can successfully estimate strains and landing loads with sufficient accuracy.

Estimation of Maximum Strains and Loads in Aircraft Landing Using Artificial Neural Network

In this work, an efficient aircraft landing simulation strategy is proposed to develop an efficient and reliable hard-landing monitoring procedure. Landing stage is the most dangerous moment during operation cycle of aircraft and it may cause structural damage when hard-landing occurs. Therefore, the occurrence of hard-landing should be reported accurately to guarantee the structural integrity of aircraft. In order to accurately determine whether hard-landing occurs or not from given landing conditions, full nonlinear structural dynamic simulation can be performed, but this approach is highly timeconsuming. Thus, a more efficient approach for aircraft landing simulation which uses a hierarchical aircraft landing model and an extended inertia relief technique is proposed. The proposed aircraft landing model is composed of a multi-body dynamics model equipped with landing gear and tire models to extract the impact force and inertia force at touch-down and a linear dynamic structural model with an extended inertia relief method to analyze the structural response subject to the prescribed rigid body motion and the forces extracted from the multi-body dynamics model. The numerical examples show the efficiency and practical advantages of the proposed landing model as an essential component of aircraft hard-landing monitoring procedure.

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Hard-landing Simulation by a Hierarchical Aircraft Landing Model and an Extended Inertia Relief Technique

In this paper, a method for the estimation of structural displacements using structure's mode shapes and accelerations is suggested to reduce the disadvantages of acceleration time integration method. Acceleration time integration method requires accurate information on initial conditions, and errors caused by noise can be accumulated during time integration. To avoid these problems, the method for the estimation of structural displacements based on mode superposition method is developed and two vibration experiments for cantilever beam are conducted to verify this method. Static displacements and dynamic displacements of beam structure are estimated using measured accelerations from experiments and mode shapes of cantilever beam, and they are compared with measured displacements using laser displacement sensor. From these results, the validity and usefulness of this method are verified.

Estimation of Structural Displacements for Cantilever Beam Using Mode Shapes and Accelerometers Under Free Vibration

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

https://www.koreascience.kr:443/article/JAKO201819355173830.pdf

Kyu Beom Lee

Papers

Hard-landing Simulation by a Hierarchical Aircraft Landing Model and an Extended Inertia Relief Technique

Estimation of Maximum Strains and Loads in Aircraft Landing Using Artificial Neural Network

Estimation of Structural Displacements for Cantilever Beam Using Mode Shapes and Accelerometers Under Free Vibration

A Study on Parallel Performance Optimization Method for Acceleration of High Resolution SAR Image Processing